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HESS | Articles | Volume 23, issue 1
Hydrol. Earth Syst. Sci., 23, 447–463, 2019
https://doi.org/10.5194/hess-23-447-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 23, 447–463, 2019
https://doi.org/10.5194/hess-23-447-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 25 Jan 2019

Research article | 25 Jan 2019

Statistical approaches for identification of low-flow drivers: temporal aspects

Anne Fangmann and Uwe Haberlandt

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Cited articles

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de Wit, M. J. M., van den Hurk, B., Warmerdam, P. M. M., Torfs, P. J. J. F., Roulin, E., and van Deursen, W. P. A.: Impact of climate change on low-flows in the river Meuse, Climatic Change, 82, 351–372, https://doi.org/10.1007/s10584-006-9195-2, 2007. 
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Low-flow events are little dynamic in space and time. Thus, it is hypothesized that models can be found, based on simple statistical relationships between low-flow metrics and meteorological states, that can help identify potential low-flow drivers. In this study we assess whether such relationships exist and whether they can be applied to predict future low flow within regional climate change impact assessment in the northwestern part of Germany.
Low-flow events are little dynamic in space and time. Thus, it is hypothesized that models can...
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